watershed.add_mass_linkage(updown)
watershed.add_outlet('101')
# names of the files used in the simulation (the HSPF input and output files
# are generated automatically); can also specify a directory to use elsewhere
filename = 'example06'
wdmoutfile = filename + '_out.wdm'
# create an instance of the HSPFModel class
hspfmodel = HSPFModel()
# and build the model from the watershed
hspfmodel.build_from_watershed(watershed, filename, tstep=tstep)
# add a special action, thawed ground on the agricultural land
# in the first subbasin on April 1 at 12 noon.
thawdate = datetime.datetime(2001, 4, 1, 12)
hspfmodel.add_special_action('thaw', '100', 'Agriculture', thawdate)
# add another special action, frozen ground on the agricultural land
# in the first subbasin on December 1 at midnight.
freezedate = datetime.datetime(2001, 12, 1)
hspfmodel.add_special_action('frozen', '100', 'Agriculture', freezedate)
# the observed flow is dsn 281
oflow = wdm.get_data(f, 281, start = start, end = end)
# close up the wdm file (forgetting this WILL cause trouble)
wdm.close('hunting.wdm')
# make a list of the times in the daily time series using datetime "timedelta"
delta = datetime.timedelta(days = 1)
times = [start + i * delta for i in range(len(precip))]
# build the model (file will all be called example02)
hspfmodel.build_from_watershed(watershed, 'example02', ifraction = ifraction,
tstep = tstep)
# now add the time series to the model
hspfmodel.add_timeseries('precipitation', 'hunting_prec', start, precip,
tstep = tstep)
hspfmodel.add_timeseries('evaporation', 'hunting_evap', start, evap,
tstep = tstep)
# and assign the time series to all the operations in the watershed
hspfmodel.assign_watershed_timeseries('precipitation', 'hunting_prec')
hspfmodel.assign_watershed_timeseries('evaporation', 'hunting_evap')
# this simulation used the hydrology modules (and no others); need to create the
# operations for the model and the default values for the hydrology parameters
# model filename + '_in.wdm' for the input WDM file and '_out.wdm' for the
# output file (we'll need this later to retrieve results from the files)
wdmoutfile = filename + '_out.wdm'
# let's also generate an optional output file created by HSPF directly
outfile = filename + '.out'
# create an instance of the HSPFModel class
hspfmodel = HSPFModel()
# and build the model from the watershed
hspfmodel.build_from_watershed(watershed, filename, print_file = outfile,
tstep = tstep)
# to run a simulation it is necessary to assign precipitation, potential
# evapotranspiration, and any other time series to the subbasins.
# there are many different ways to estimate the potential evapotranspiration
# including correlation to observed pan evaporation, Penman-Monteith, etc.
# here the potential evapotranspiration is assumed to start at zero then
# increase to 12 mm in a day 7/01, then decreases to zero 1/01; thus max 4-hr
# potential evapotranspiration is 2 mm. the following statement will generate
# a time series with these assumptions.
maxET = 2
nsteps = (end-start).days * 1440 // tstep
evaporation = [maxET * (d - datetime.datetime(d.year, 1, 1)).days /
(datetime.datetime(d.year, 7, 1) -
datetime.datetime(d.year, 1, 1)).days
watershedSiletz.add_outlet(str(basin + 1)) # Assumes basin numbers
x = 1 # Don't need this but the loop wants to include 'hspfmodel...'
# Build the model
hspfmodel = HSPFModel(units='Metric')
filename = 'siletz_river'
outfile = filename + '.out'
wdmoutfile = filename + '_out.wdm'
hspfmodel.build_from_watershed(watershedSiletz,
'siletz_river',
ifraction=ifraction,
tstep=tstep,
print_file=outfile)
watershedSiletz.plot_mass_flow(output='siletz_basin_network')
# ADD TIME SERIES DATA: PRECIP, PET, and FLOW TO THE WDM FILE
pcpData = pd.read_csv(
os.path.abspath(os.path.curdir) + '\\siletz_HSPF_precip.csv')
petData = pd.read_csv(
os.path.abspath(os.path.curdir) + '\\siletz_HSPF_pet.csv')
flwData = pd.read_csv(
os.path.abspath(os.path.curdir) + '\\siletz_HSPF_flw.csv')
watershed.add_mass_linkage(updown)
watershed.add_outlet('101')
# names of the files used in the simulation (the HSPF input and output files
# are generated automatically); can also specify a directory to use elsewhere
filename = 'example06'
wdmoutfile = filename + '_out.wdm'
# create an instance of the HSPFModel class
hspfmodel = HSPFModel()
# and build the model from the watershed
hspfmodel.build_from_watershed(watershed, filename, tstep = tstep)
# add a special action, thawed ground on the agricultural land
# in the first subbasin on April 1 at 12 noon.
thawdate = datetime.datetime(2001, 4, 1, 12)
hspfmodel.add_special_action('thaw', '100', 'Agriculture', thawdate)
# add another special action, frozen ground on the agricultural land
# in the first subbasin on December 1 at midnight.
freezedate = datetime.datetime(2001, 12, 1)
hspfmodel.add_special_action('frozen', '100', 'Agriculture', freezedate)
evap = [0] + [e / 24 for e in evap for i in range(24)]
precip = [0] + [p for p in precip]
oflow = [0] + [o for o in oflow]
# list of times
times = [start + (end - start) / len(precip) * i for i in range(len(precip))]
# make the HSPFModel instance
hspfmodel = HSPFModel(units='English')
# build the model (file will all be called example03)
hspfmodel.build_from_watershed(watershed,
'example03',
ifraction=ifraction,
tstep=tstep)
# now add the time series to the model
hspfmodel.add_timeseries('precipitation',
'hunting_prec',
start,
precip,
tstep=60)
hspfmodel.add_timeseries('evaporation', 'hunting_evap', start, evap, tstep=60)
hspfmodel.add_timeseries('flowgage', 'hunting_flow', start, oflow, tstep=60)
# and assign the watershed time series to all the operations
hspfmodel.assign_watershed_timeseries('precipitation', 'hunting_prec')
# output file (we'll need this later to retrieve results from the files)
wdmoutfile = filename + '_out.wdm'
# let's also generate an optional output file created by HSPF directly
outfile = filename + '.out'
# create an instance of the HSPFModel class
hspfmodel = HSPFModel()
# and build the model from the watershed
hspfmodel.build_from_watershed(watershed,
filename,
print_file=outfile,
tstep=tstep)
# to run a simulation it is necessary to assign precipitation, potential
# evapotranspiration, and any other time series to the subbasins.
# there are many different ways to estimate the potential evapotranspiration
# including correlation to observed pan evaporation, Penman-Monteith, etc.
# here the potential evapotranspiration is assumed to start at zero then
# increase to 12 mm in a day 7/01, then decreases to zero 1/01; thus max 4-hr
# potential evapotranspiration is 2 mm. the following statement will generate
# a time series with these assumptions.
maxET = 2
nsteps = (end - start).days * 1440 // tstep
evaporation = [
maxET * (d - datetime.datetime(d.year, 1, 1)).days /
